Evidence map›Paper›PMID 41187143›Full record

ArticlePLoS medicine2025

Combining demographic shifts with age-based resistance prevalence to estimate future antimicrobial resistance burden in Europe and implications for targets: A modelling study.

Naomi R Waterlow, Clare I R Chandler, Ben S Cooper, Catrin E Moore, Julie V Robotham, Benn Sartorius, Michael Sharland, Gwenan M Knight

Abstract read
In one paragraph

Article in PLoS medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. [Pharmacokinetic and metabolic considerations of antibiotic usage in children and the elderly].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Naomi R WaterlowCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Clare I R ChandlerAMR Centre, London School of Hygiene and Tropical Medicine, London, United Kingdom.ORCID https://orcid.org/0000-0001-6499-7522
Ben S CooperCentre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Catrin E MooreInstitute of Infection and Immunity, City St George's, University of London, London, United Kingdom.ORCID https://orcid.org/0000-0002-8639-9846
Julie V RobothamAMR and HCAI Division, Chief Medical Advisor's Group, UKHSA, London, United Kingdom.
Benn SartoriusUniversity of Queensland Centre for Clinical Research (UQCCR), Faculty of Health, Medicine and Behavioural Sciences, University of Queensland, Brisbane, Queensland, Australia.ORCID https://orcid.org/0000-0001-6761-2325
Michael SharlandInstitute of Infection and Immunity, City St George's, University of London, London, United Kingdom.
Gwenan M KnightCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.ORCID https://orcid.org/0000-0002-7263-9896

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAntimicrobial Resistance (AMR) is a global public health crisis. Evaluating intervention impact requires accurate estimates of how the AMR burden will change over time, given likely demographic shifts. This study aimed to provide an estimate of future AMR burden in Europe, investigating resistance variation by age and sex and the impact of interventions to achieve the proposed United Nations (UN) political declaration targets. METHODS AND

findingsUsing data from 12,807,473 bloodstream infection (BSI) susceptibility tests from routine surveillance in Europe, we estimate age- and sex-specific rates of change in BSI incidence for the 8 bacteria included in European Antimicrobial Resistance Surveillance Network (EARS-Net) surveillance over 2015-2019. This was used to project incidence rates by age and sex for 2022-2050 and, with demographic projections, to generate estimates of BSI burden (2022-2050). Two Bayesian hierarchical models were fitted across 38 bacteria-antibiotic combinations to the 2015-2019 resistance proportion of BSI by year and at the country-level with and without age and sex disaggregation. Inputting the incidence estimates into the "agesex" and "base" model, respectively, we sampled 1,000 model estimates of resistant BSI burden by age, sex, and country to determine the importance of age and sex disaggregation. We explored Intervention scenarios consisting of a 1, 5, or 20 per 100,000 per year reduction in infection incidence rate of change or 5 per 100,000 per year reduction in those older than 64 years. Overall, in Europe, BSI incidence rates are predicted to increase more in men than women across 6 of the 8 bacteria (Pseudomonas aeruginosa and Enterococcus faecium were the exception) and are projected to increase more dramatically in older age groups (74+ years) but stabilise or decline in younger age groups. We project huge country-level variation in resistance burden to 2050, with opposing trends in different countries for the same bacteria-antibiotic combinations (e.g., aminoglycoside-resistant Acinetobacter spp. ranged from a relative difference of 0.34 to 15.38 by 2030). Not accounting for age and sex results in differing resistance burden projections, with 47% of bacteria-antibiotic combinations estimated to have fewer resistant BSIs by 2030 compared to a model with age and sex. Not including age or sex resistance patterns results in fewer male cases for 76% (29/38) of the combinations compared to 11% (4/38) for women. We also saw age-based associations in projections with bigger differences at older ages. Achieving a 10% reduction in resistant BSI incidence by 2030 (equivalent to the UN 10% mortality target) was possible only for 68.4% (26/38) of bacteria-antibiotic combinations even with large reductions in BSI incidence rate of change of -20 per 100,000 per year. In some cases, a 10% reduction was followed by a rebound, with the resistant BSI burden exceeding previous levels by 2050. Limitations include reliance on European data and current trends, and the exclusion of factors such as comorbidities or ethnicity.

conclusionsIncluding country-specific, age- and sex-specific resistance levels alongside projected demographic shifts has a large impact on resistant BSI burden projections in Europe to 2030. Reducing this AMR infection burden by 10% will require substantial reductions in infection incidence rates.

Indexed as

Anti-Bacterial AgentsBacteremiaDrug Resistance, BacterialAdolescentAdultAgedAged, 80 and overAge FactorsBayes TheoremChildChild, PreschoolEuropeFemaleHumansIncidenceInfantAnti-Bacterial Agents

Identifiers

PMID41187143
PMCPMC12585039

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.